123 research outputs found
Graph Reconstruction via Distance Oracles
We study the problem of reconstructing a hidden graph given access to a
distance oracle. We design randomized algorithms for the following problems:
reconstruction of a degree bounded graph with query complexity
; reconstruction of a degree bounded outerplanar graph with
query complexity ; and near-optimal approximate reconstruction of
a general graph
Large Deviations for Random Trees
We consider large random trees under Gibbs distributions and prove a Large
Deviation Principle (LDP) for the distribution of degrees of vertices of the
tree. The LDP rate function is given explicitly. An immediate consequence is a
Law of Large Numbers for the distribution of vertex degrees in a large random
tree. Our motivation for this study comes from the analysis of RNA secondary
structures.Comment: 10 page
A Combinatorial Framework for Designing (Pseudoknotted) RNA Algorithms
We extend an hypergraph representation, introduced by Finkelstein and
Roytberg, to unify dynamic programming algorithms in the context of RNA folding
with pseudoknots. Classic applications of RNA dynamic programming energy
minimization, partition function, base-pair probabilities...) are reformulated
within this framework, giving rise to very simple algorithms. This
reformulation allows one to conceptually detach the conformation space/energy
model -- captured by the hypergraph model -- from the specific application,
assuming unambiguity of the decomposition. To ensure the latter property, we
propose a new combinatorial methodology based on generating functions. We
extend the set of generic applications by proposing an exact algorithm for
extracting generalized moments in weighted distribution, generalizing a prior
contribution by Miklos and al. Finally, we illustrate our full-fledged
programme on three exemplary conformation spaces (secondary structures,
Akutsu's simple type pseudoknots and kissing hairpins). This readily gives sets
of algorithms that are either novel or have complexity comparable to classic
implementations for minimization and Boltzmann ensemble applications of dynamic
programming
Graph Transformation in Molecular Biology
In the beginning, one of the main fields of application of graph transformation was biology, and more specifically morphology. Later, however, it was like if the biological applications had been left aside by the graph transformation community, just to be moved back into the mainstream these very last years with a new interest in molecular biology. In this paper, we review several fields of application of graph grammars in molecular biology, including: the modeling higherdimensional structures of biomolecules, the description of biochemical reactions, the analysis of metabolic pathways, and their potential use in computational systems biology
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